Background
Monoclonal antibody (mAb) therapy has revolutionized the treatment of a vast range of diseases, mostly in the areas of oncology and autoimmune/inflammatory disorders[1]. With a world market exceeding 60 billion USD per year and six mAb related products in the top 10 selling drugs, the industry continues to grow at a fast rate[2]. Chinese hamster ovary (CHO) cells are the preferred production host for therapeutic production of mAbs due to their efficiency in performing post-translational modifications and their ability to produce proteins with similar properties to native human proteins[3]. Surprisingly, despite products varying only by a few amino acids in the variable region of a MAb, each production cell line is still developed by generating and screening a large strain pool, and generally the production process has to be reoptimised.
Systems biology can be used as a powerful tool for the identification of key markers of good production lines, with the aim of engineering superior host lines that more reliably produce good production clones. To date systems biology efforts have been hampered by the need to use the mouse, rat and/or human genome as a reference and has suffered from the inherent limitation in coverage of 2-dimensional gel electrophoresis or mouse or CHO cDNA microarrays. The development of new techniques such as RNA sequencing for transcriptome analysis and LC-MS/MS for proteome analysis combined with the recent release of the CHO genome has reignited interest in using quantitative proteomics and transcriptomics to study high productivity cell lines.